Activity levels during inpatient stroke rehabilitation
429
Table II. Demographic data and clinical characteristics of individuals
with stroke (n = 26).
Characteristics Stroke
Age, years, mean (SD)
Female, n (%)
Days since stroke, mean (SD)
Ischaemic stroke, n (%)
Haemorrhagic stroke, n (%)
Right hemiparesis, n (%)
Right hand dominant, n (%)
Left hand dominant, n (%)
Bimanual, n (%)
Dependent in walking (FAC 0–3), n (%)
Independent in walking (FAC 4–5), n (%)
Arm impairment (FMA-UE, 0–66), median (Q1–Q3)
Decreased sensation UE (≤ 11 FMA-UE), n (%)
Decreased PROM UE (≤ 23 FMA-UE), n (%)
Pain UE (≤ 23 FMA-UE), n (%)
Leg impairment (FMA-LE, 0–34), median (Q1–Q3)
Decreased sensation LE (≤ 11 FMA-LE), n (%)
Decreased PROM LE (≤ 19 FMA-LE), n (%)
Pain LE (≤ 19 FMA-LE), n (%)
Spasticity, elbow/wrist (≥ 1 MAS), n (%)
Spasticity, ankle (≥ 1 MAS), n (%) 55.4 (11.0)
10 (38.5)
56 (24)
21 (81)
5 (19)
13 (50)
22 (85)
2 (8)
2 (8)
13 (50)
13 (50)
35 (15–50)
19 (73)
22 (85)
14 (54)
20 (17–26)
22 (85)
22 (85)
4 (15)
19 (73)
16 (61)
SD: standard deviation; FAC: Functional Ambulation Categories; FMA-UE:
Fugl-Meyer Assessment Upper Extremity; FMA-LE: Fugl-Meyer Assessment
Lower Extremity; PROM: passive range of motion; UE: upper extremity; LE:
lower extremity.
(Table I). Data from all 5 sensors during a weekend
measurement session (1.4% of total 360 measurements)
was missing since the patient forgot to apply the sensors
(human factor). All other data loss was due to technical
failure and random (10.5%). Thus, in all collected data
including measurements from the 2 excluded participants
(380 measurements) human error accounted for 3.9% and
technical failure for 12.6% of missing/incomplete data.
Common technical failures were malfunction of battery
or memory card, failure of wireless synchronization bet-
ween the sensors or failure occurring during data transfer.
The demographic and clinical characteristics of the
individuals with stroke are shown in Table II. The control
group included 10 individuals (4 men, 6 women) between
32 and 64 years (mean 50.6 years, SD 11.8). All healthy
controls were right-hand dominant. The FMA scores of
upper and lower extremities ranged between 7–65 and
8–33, respectively, which indicates that persons with
both low and high sensorimotor function were included.
The activity logs showed that participants with stroke
spent approximately 70% of the daytime in sitting (Fig.
1). The time in sitting activities was comparable between
weekdays and weekends, but slightly more time was spent
in standing/walking on weekdays (19%) and slightly more
time in lying/resting at weekends (20%). Among healthy
controls, 63% was spent in sitting, 36% in standing/
walking activities, and almost nothing in lying or resting
on weekdays (workdays). At weekends, however, 12%
was spent in lying/resting and 44% of time was equally
spent in sitting or standing/walking activities.
The main reported activities in stroke were eating,
watching TV, rest, walking or training, transport by car,
Fig. 1. Percentage of time spent in sitting, standing/walking or lying/
resting activities during the daytime between 08.00 h and 20.00 h,
based on the reported activity logs.
light household activities and shopping, computer gaming,
social activities such as meeting and talking with others,
playing with children. Among the healthy controls, 5
were working in an office environment and 5 had clinical
work in hospital setting. The main activities on weekdays
reported by the controls were: working with the computer,
clinical work with patients, meetings, shopping, making
food, driving, using public transport, cycling, and oc-
casional training (biking, gym, yoga). On weekends the
activities reported were: shopping, driving, household
activities, cultural activities, such as going to a museum,
concert, and coffee shop, reading, studying, watching TV,
walking, working in the garden and ice-skating.
Differences in activity levels on weekdays and
weekends
Participants with stroke showed lower arm and leg activity
at weekends compared with weekdays (Table III, Fig. 2A
and 2B). The largest difference between weekdays and
weekend was observed for the affected arm (z = 3.67,
p < 0.001, r = 0.57) followed by the less-affected leg
(r = 0.41), less-affected arm (r=0.37) and affected leg
activity (r = 0.32). As expected, participants with stroke
used their more-affected arm less compared with the
less-affected arm at both sessions (z = 3.95/3.82, p < 001,
r = 0.59/0.62). This difference was also reflected in the arm
ratio measure (Table III, Fig. 2C), which showed larger
asymmetry at weekends (z = 2.07, p < 0.05, r = 0.32). This
indicates that the participants with stroke relied even more
on their less-affected arm during normal daily activities at
weekends. There was no interaction effect between arm
activity and hand dominance of the affected arm (p > 0.37).
J Rehabil Med 51, 2019